Integrated Lean-Six Sigma for Flexible Manufacturing Cells: Design, Implementation, and Evaluation

Thesis Abstract

This study addresses the persistent inefficiencies in traditional dedicated manufacturing lines by integrating Lean and Six Sigma principles within Flexible Manufacturing Cells (FMCs) to enhance adaptability, throughput, and quality while reducing waste and variation. The aim is to design an integrated Lean-Six Sigma (ILSS) framework tailored for FMCs, implement it in a real-world production environment, and evaluate its impact on operational performance, process capability, and workforce engagement. Specific objectives are (i) to develop a hybrid ILSS framework combining value stream mapping, standard work, and DMAIC-driven process improvement for FMCs; (ii) to engineer a modular cell layout and standardized work instructions compatible with variable product mix; (iii) to implement takt-based scheduling, SMED, and poka-yoke mechanisms to achieve rapid changeover and defect reduction; (iv) to quantify improvements using statistical process control, capability indices (Cp, Cpk), and economic impact; (v) to assess organizational readiness and employee engagement as mediating factors; and (vi) to formulate a practical roadmap for scale-up to multi-cell environments. The methodology adopts a mixed-methods approach within a pragmatist paradigm. The research design combines a quasi-experimental, pre-post intervention with a control FMC to isolate the effects of the ILSS framework. The population comprises 12 FMCs within a mid-sized automotive supplier and associated supplier networks, with an intervention sample of six cells and a control sample of six cells. Data collection instruments include standardized process capability assessments, time-and-motion studies, value stream mapping reports, Likert-scale surveys on employee engagement, and interview guides for frontline operators and supervisors. Instrument validity and reliability are ensured through content validity by a panel of operations management and industrial engineering experts and pilot testing with two FMCs. Data analysis employs both quantitative and qualitative techniques regression analysis and ANOVA to evaluate changes in throughput, cycle time, defect rate, and Cpk; SPC charts to track process stability; IPA (importance-performance analysis) to prioritize improvement actions; and thematic analysis of interview transcripts to uncover enablers and barriers to ILSS adoption. A conceptual model linking Lean waste elimination, Six Sigma variation reduction, and FMC flexibility will be tested, drawing on the theories of Delone and McLean’s Information System Success for technology-enabled process improvements and the Dynamic Capability framework to explain organizational adaptation. Expected findings include statistically significant reductions in cycle time (14–22%), defect rate (28–40%), and changeover time (SMED target of 60–90 minutes reduced by 55%), accompanied by improvements in process capability indices (Cpk > 1.33) and a measurable uplift in OEE (overall equipment effectiveness) by 12–18%. Economically, anticipated annualized savings are projected at 15–25% of direct manufacturing costs, driven by waste reduction, shorter lead times, and reduced downtime. The study contributes to knowledge by operationalizing an integrative ILSS framework specifically for FMCs, clarifying the interactions between Lean and Six Sigma in a flexible, high-mix environment, and detailing a replicable implementation recipe anchored in empirical evidence. It also extends the Dynamic Capability perspective by illustrating how organizational routines and worker empowerment enable rapid reconfiguration of manufacturing cells in response to demand variability. The main conclusion posits that the ILSS framework substantially enhances performance while maintaining quality under high product diversity, provided that changeover improvements, standardized work, and employee involvement are sustained through structured training and visible management support. Recommendations include adopting a phased rollout of ILSS modules across additional FMCs, investing in digital sensing and real-time analytics to support SPC and decision-making, establishing cross-functional improvement teams, and integrating ILSS practices with supplier collaboration programs to maximize end-to-end efficiency.